Domestication has had a strong impact on the development of modern societies. We sequenced 200 genomes of the chocolate plant Theobroma cacao L. to show for the first time that a single population underwent strong domestication approximately 3,600 years (95% CI: 2481 – 10,903 years ago) ago, the Criollo population. We also show that during the process of domestication, there was strong selection for genes involved in the metabolism of the colored protectants anthocyanins and the stimulant theobromine, as well as disease resistance genes. Our analyses show that domesticated populations of T. cacao (Criollo) maintain a higher proportion of high frequency deleterious mutations. We also show for the first time the negative consequences the increase accumulation of deleterious mutations during domestication on the fitness of individuals (significant negative correlation between Criollo ancestry and Kg of beans per hectare per year, P = 0.000425).
PRDM9 drives recombination hotspots in some mammals, including mice and apes. Non-functional orthologs of PRDM9 are present in a wide variety of vertebrates, but why it is functionally maintained in some lineages is not clear. One possible explanation is that PRDM9 plays a role in ensuring that meiosis is successful. During meiosis, available DNA may be a limiting resource given the tight packaging of chromosomes and could lead to competition between two key processes: meiotic transcription and recombination. Here we explore this potential competition and the role that PRDM9 might play in their interaction. Leveraging existing mouse genomic data, we use resampling schemes that simulate shuffled features along the genome and models that account for the rarity of features in the genome, to test if PRDM9 influences interactions between recombination hotspots and meiotic transcription in a whole genome framework. We also explored possible DNA sequence motifs associated to clusters of hotspots not tied to transcription or PRDM9. We find evidence of competition between meiotic transcription and recombination, with PRDM9 appearing to relocate recombination to avoid said conflict. We also find that retrotransposons may be playing a role in directing hotspots in the absence of other factors.
Reduced representation sequencing methods such as genotyping-by-sequencing (GBS) enable low-cost measurement of genetic variation without the need for a reference genome assembly. These methods are widely used in genetic mapping and population genetics studies, especially with nonmodel organisms. Variant calling error rates, however, are higher in GBS than in standard sequencing, in particular due to restriction site polymorphisms, and few computational tools exist that specifically model and correct these errors. We developed a statistical method to remove errors caused by restriction site polymorphisms, implemented in the software package GBStools. We evaluated it in several simulated data sets, varying in number of samples, mean coverage and population mutation rate, and in two empirical human data sets (N = 8 and N = 63 samples). In our simulations, GBStools improved genotype accuracy more than commonly used filters such as Hardy-Weinberg equilibrium pvalues. GBStools is most effective at removing genotype errors in data sets over 100 samples when coverage is 40X or higher, and the improvement is most pronounced in species with high genomic diversity. We also demonstrate the utility of GBS and GBStools for human population genetic inference in Argentine populations and reveal widely varying individual ancestry proportions and an excess of singletons, consistent with recent population growth. Author SummaryEukaryotic genomes range from millions to billions of base pairs in size, but for many genetic experiments it is sufficient to gather information from just a fraction of these sites. In practice, selecting a consistent set of sites can be achieved by cutting genomic DNA with enzymes that recognize DNA sequence motifs, and then sequencing the ends of the resulting fragments. The advantages of this wellknown approach are its low cost relative to whole-genome sequencing (WGS), and that it does not require a sequenced genome. These methods, for example genotyping-by-sequencing (GBS), are popular for mapping genes and studying population genetics, particularly in non-model organisms.. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/030494 doi: bioRxiv preprint first posted online Nov. 3, 2015; 3 Here we demonstrate, however, that computational tools designed for WGS are insufficient for handling certain error types that arise in GBS and other similar methods. We present a modified protocol for GBS and a statistical method for detecting these errors, implemented in the software package GBStools. We tested our methods on human DNA samples from Argentine populations. Our results reveal widely varying degrees of European and Native American ancestry, and that rare genetic variants are more numerous than would be expected in a population with constant size.
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